A conventional real-time spectrum analyzer generally receives a time domain input signal from a device under test (DUT) and displays corresponding frequency domain spectra, where each frequency domain spectrum represents a corresponding time interval. The spectra may be obtained by performing fast Fourier transforms (FFTs) on digital time domain data representing the time domain input signal.
In a conventional real-time spectrum analyzer, the signal from the DUT is first digitized and provided to an acquisition control unit. The acquisition control unit may use internal or external trigger inputs, including a frequency mask trigger, for example, to determine whether or not to acquire new data. The acquired time domain data are converted into the frequency domain data, which is processed for display using various visualization algorithms.
The frequency mask trigger included in the conventional real-time spectrum analyzer provides triggered measurements and/or displays. The frequency mask trigger is configured to detect a trigger condition in the spectra based on a frequency mask having various levels fixed to absolute frequency points. When the trigger condition is detected, a fixed amount of the frequency domain data displayed (and stored), and then the trigger is re-armed. Although a real-time spectrum analyzer makes it relatively easy to isolate specific occurrences, it does not provide the ability to easily separate specific events from a complex signal stream when those events are not clearly separated in frequency from other events. When such events are not clearly separated in frequency, a user must provide program the real-time spectrum analyzer for custom analysis, reprogram the DUT and/or change the test environment, so that the specific events can be easily separated from other signal events.